IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

  • Konstantin A. Kholodilin

    ()

    (DIW Berlin)

  • Boriss Siliverstovs

    ()

    (DIW Berlin)

In this paper we perform a comparative study of the forecasting properties of the about 30 alternative leading indicators for Germany using the growth rates of German real GDP. In addition to them, we have constructed a diffusion index based on the principal component analysis and including 145 component series that reflect all the facets of German economy. We use the post-unification data which cover years from 1991 through 2004. Using a battery of statistical tests we detect a structural break in the growth rates that occurs in the first half of 2001. Our results suggest that the forecasting ability of the leading indicators has been rather good in the pre-break period with our diffusion index showing the superior forecasting accuracy but the forecasting performance of all alternative indicators has significantly deteriorated in the post-break period, i.e. in 2001-2004. None of the leading indicator models was able to predict and accommodate the structural break in the growth rates of the time series under scrutiny. This finding confirms the widespread impression among the practitioners that the state of German economy in the recent years became much more difficult to forecast.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.wiso-net.de/webcgi?START=A60&DOKV_DB=ZECO&DOKV_NO=JFNSJFNS2006050023424232917141524271&DOKV_HS=0&PP=1
File Function: Main text
Download Restriction: Access via GENIOS - German Business Information - http://www.genios.de/r_startseite/index.ein

File URL: http://search.ebscohost.com/login.aspx?direct=true&db=ecn&AN=0870472&site=ehost-live
File Function: Main text
Download Restriction: Access via EBSCOhost Econlit - http://www.ebscohost.com/

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Justus-Liebig University Giessen, Department of Statistics and Economics in its journal Journal of Economics and Statistics.

Volume (Year): 226 (2006)
Issue (Month): 3 (May)
Pages: 234-259

as
in new window

Handle: RePEc:jns:jbstat:v:226:y:2006:i:3:p:234-259
Contact details of provider: Postal: Licher Straße 74, 35394 Gießen
Phone: +49 (0)641 99 22 001
Fax: +49 (0)641 99 22 009
Web page: http://wiwi.uni-giessen.de/home/oekonometrie/Jahrbuecher/

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
  2. Anindya BANERJEE & Massimiliano MARCELLINO, 2002. "Are There Any Reliable Leading Indicators for US Inflation and GDP Growth?," Economics Working Papers ECO2002/21, European University Institute.
  3. Ulrich Fritsche & Sabine Stephan, 2000. "Leading Indicators of German Business Cycles: An Assessment of Properties," Macroeconomics 0004005, EconWPA.
  4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  5. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers.
  6. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  7. Christian Dreger & Christian Schumacher, 2005. "Out-of-sample Performance of Leading Indicators for the German Business Cycle: Single vs. Combined Forecasts," Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2005(1), pages 71-87.
  8. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  9. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  10. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  11. Marc Brisson & Bryan Campbell & John Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
  12. Schröder, Michael & Hüfner, Felix P., 2002. "Forecasting economic activity in Germany: how useful are sentiment indicators?," ZEW Discussion Papers 02-56, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  13. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
  14. Christian Kleiber & Achim Zeileis, 2005. "Validating multiple structural change models-a case study," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 685-690.
  15. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  16. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2001. "Strucchange: An R package for testing for structural change in linear regression models," Technical Reports 2001,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  17. George Kapetanios & Massimiliano Marcellino, 2009. "A parametric estimation method for dynamic factor models of large dimensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 208-238, 03.
  18. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2004. "The generalized dynamic factor model consistency and rates," Journal of Econometrics, Elsevier, vol. 119(2), pages 231-255, April.
  19. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  20. Donald W.K. Andrews & Inpyo Lee & Werner Ploberger, 1992. "Optimal Changepoint Tests for Normal Linear Regression," Cowles Foundation Discussion Papers 1016, Cowles Foundation for Research in Economics, Yale University.
  21. Dreger, Christian & Schumacher, Christian, 2002. "Estimating large-scale factor models for economic activity in Germany : do they outperform simpler models?," HWWA Discussion Papers 199, Hamburg Institute of International Economics (HWWA).
  22. Shintani, Mototsugu, 2005. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 517-38, June.
  23. Ivan Paya & Agustín Duarte & Ioannis A. Venetis, 2004. "Predicting Real Growth And The Probability Of Recession In The Euro Area Using The Yield Spread," Working Papers. Serie AD 2004-31, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  24. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  25. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo Group Munich.
  26. Israel Sancho & maximo Camacho, 2002. "Spanish diffusion indexes," Computing in Economics and Finance 2002 276, Society for Computational Economics.
  27. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  28. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
  29. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
  30. Erich Langmantel, 1999. "Das ifo Geschäftsklima als Indikator für die Prognose des Bruttoinlandsprodukts," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 52(16-17), pages 16-21, October.
  31. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:jns:jbstat:v:226:y:2006:i:3:p:234-259. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Winker)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.